Director, Applied AI & Analytics Engineering

Carrum Health•,

12h•Remote

About The Position

At Carrum, we are transforming how we pay for, deliver and experience healthcare. We are adding a Director, Applied AI & Analytics Engineering to be a senior, hands-on leader responsible for building and running Carrum's Data Science and Analytics Engineering capabilities. You will lead a team of data scientists and analytics engineers, setting technical direction, owning the analytics roadmap, and personally contributing to the modeling, analysis, and data architecture work the team delivers. This is a player-coach role: you write code, build models, and review pull requests as much as you set strategy and develop people. You will define how data is modeled, measured, and made accessible across the organization, and partner with Product and Engineering to embed AI, data science and ML directly into the Carrum platform. The business will look to you to make Carrum measurably smarter: sharper member and care team intelligence, more precise financial and revenue cycle analytics, CRM and funnel optimization that drives conversion, and AI capabilities that meaningfully improve how care is navigated and delivered.

Requirements

12+ years in data science or analytics engineering.
At least 3 years leading teams in a healthcare or regulated industry setting.
Hands-on practitioner: write production-quality Python or SQL, build and deploy models.
Deep experience with healthcare data environments: HIPAA/PHI compliance, claims data, episode-level analytics, and accuracy/auditability standards.
Proven experience in finance analytics or revenue cycle management, including revenue recognition, cost tracking, claims reconciliation, and financial reporting infrastructure.
Strong analytics engineering foundation: data modeling, dbt or equivalent transformation tooling, semantic layer design, and self-serve analytics at scale.
Track record delivering production-grade AI, ML and data science solutions, from problem framing through deployment, monitoring, and iteration.
Experience building member or customer funnel analytics, propensity and segmentation models, and next best action frameworks that drive measurable conversion or engagement outcomes.
Strong communicator who can translate complex analytical work into clear executive narratives and hold their own in WBRs and leadership forums.

Nice To Haves

Experience with value-based care, specialty care, employer health benefits, or care navigation in a digital health environment.
Familiarity with CRM data integration and analytics, including pipeline modeling, outreach prioritization, and conversion attribution.
Background in MLOps and model governance including deployment pipelines, monitoring, drift detection, and audit trails in regulated environments.
Experience with experimentation platforms and causal inference methods applied to member engagement or operational programs.
Experience evaluating and integrating third-party AI vendors or data products into an existing analytics stack.

Responsibilities

Lead a team of data scientists and analytics engineers.
Set technical direction for data science and analytics engineering.
Own the analytics roadmap.
Personally contribute to modeling, analysis, and data architecture.
Define how data is modeled, measured, and made accessible across the organization.
Partner with Product and Engineering to embed AI, data science, and ML into the Carrum platform.
Make Carrum measurably smarter through improved intelligence, analytics, and AI capabilities.
Mentor team members through direct coaching, code and model reviews, and creating opportunities for growth.
Connect analysis to action by partnering with business leaders to frame questions, deliver actionable answers, and follow through on changes.
Ensure data trustworthiness by building infrastructure and culture that supports stakeholder confidence in data quality.